Understanding how bloggers feel

Abstract

One of the goals of affective computing is to recognize human emotions. We present a system that learns to recognize emotions based on textual resources and test it on a large number of blog entries tagged with moods by their authors. We show how a machine-learning approach can be used to gain insight into the way writers convey and interpret their own emotions, and provide nuanced mood associations for a large wordlist.

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